{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# PART1 数据探索 与可视化分析\n",
    "#####                                                                                      byLIJIANcoder97"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "from matplotlib import pyplot as plt\n",
    "%matplotlib inline\n",
    "import seaborn as sns\n",
    "Taitan_train=pd.read_csv('dataset/titanic/train.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 数据概览"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>PassengerId</th>\n",
       "      <th>Survived</th>\n",
       "      <th>Pclass</th>\n",
       "      <th>Name</th>\n",
       "      <th>Sex</th>\n",
       "      <th>Age</th>\n",
       "      <th>SibSp</th>\n",
       "      <th>Parch</th>\n",
       "      <th>Ticket</th>\n",
       "      <th>Fare</th>\n",
       "      <th>Cabin</th>\n",
       "      <th>Embarked</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Braund, Mr. Owen Harris</td>\n",
       "      <td>male</td>\n",
       "      <td>22.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>A/5 21171</td>\n",
       "      <td>7.2500</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Cumings, Mrs. John Bradley (Florence Briggs Th...</td>\n",
       "      <td>female</td>\n",
       "      <td>38.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>PC 17599</td>\n",
       "      <td>71.2833</td>\n",
       "      <td>C85</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>Heikkinen, Miss. Laina</td>\n",
       "      <td>female</td>\n",
       "      <td>26.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>STON/O2. 3101282</td>\n",
       "      <td>7.9250</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Futrelle, Mrs. Jacques Heath (Lily May Peel)</td>\n",
       "      <td>female</td>\n",
       "      <td>35.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>113803</td>\n",
       "      <td>53.1000</td>\n",
       "      <td>C123</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Allen, Mr. William Henry</td>\n",
       "      <td>male</td>\n",
       "      <td>35.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>373450</td>\n",
       "      <td>8.0500</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   PassengerId  Survived  Pclass  \\\n",
       "0            1         0       3   \n",
       "1            2         1       1   \n",
       "2            3         1       3   \n",
       "3            4         1       1   \n",
       "4            5         0       3   \n",
       "\n",
       "                                                Name     Sex   Age  SibSp  \\\n",
       "0                            Braund, Mr. Owen Harris    male  22.0      1   \n",
       "1  Cumings, Mrs. John Bradley (Florence Briggs Th...  female  38.0      1   \n",
       "2                             Heikkinen, Miss. Laina  female  26.0      0   \n",
       "3       Futrelle, Mrs. Jacques Heath (Lily May Peel)  female  35.0      1   \n",
       "4                           Allen, Mr. William Henry    male  35.0      0   \n",
       "\n",
       "   Parch            Ticket     Fare Cabin Embarked  \n",
       "0      0         A/5 21171   7.2500   NaN        S  \n",
       "1      0          PC 17599  71.2833   C85        C  \n",
       "2      0  STON/O2. 3101282   7.9250   NaN        S  \n",
       "3      0            113803  53.1000  C123        S  \n",
       "4      0            373450   8.0500   NaN        S  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Taitan_train.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>PassengerId</th>\n",
       "      <th>Survived</th>\n",
       "      <th>Pclass</th>\n",
       "      <th>Age</th>\n",
       "      <th>SibSp</th>\n",
       "      <th>Parch</th>\n",
       "      <th>Fare</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>891.000000</td>\n",
       "      <td>891.000000</td>\n",
       "      <td>891.000000</td>\n",
       "      <td>714.000000</td>\n",
       "      <td>891.000000</td>\n",
       "      <td>891.000000</td>\n",
       "      <td>891.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>446.000000</td>\n",
       "      <td>0.383838</td>\n",
       "      <td>2.308642</td>\n",
       "      <td>29.699118</td>\n",
       "      <td>0.523008</td>\n",
       "      <td>0.381594</td>\n",
       "      <td>32.204208</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>257.353842</td>\n",
       "      <td>0.486592</td>\n",
       "      <td>0.836071</td>\n",
       "      <td>14.526497</td>\n",
       "      <td>1.102743</td>\n",
       "      <td>0.806057</td>\n",
       "      <td>49.693429</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.420000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>223.500000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>20.125000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>7.910400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>446.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>28.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>14.454200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>668.500000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>38.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>31.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>891.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>80.000000</td>\n",
       "      <td>8.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>512.329200</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       PassengerId    Survived      Pclass         Age       SibSp  \\\n",
       "count   891.000000  891.000000  891.000000  714.000000  891.000000   \n",
       "mean    446.000000    0.383838    2.308642   29.699118    0.523008   \n",
       "std     257.353842    0.486592    0.836071   14.526497    1.102743   \n",
       "min       1.000000    0.000000    1.000000    0.420000    0.000000   \n",
       "25%     223.500000    0.000000    2.000000   20.125000    0.000000   \n",
       "50%     446.000000    0.000000    3.000000   28.000000    0.000000   \n",
       "75%     668.500000    1.000000    3.000000   38.000000    1.000000   \n",
       "max     891.000000    1.000000    3.000000   80.000000    8.000000   \n",
       "\n",
       "            Parch        Fare  \n",
       "count  891.000000  891.000000  \n",
       "mean     0.381594   32.204208  \n",
       "std      0.806057   49.693429  \n",
       "min      0.000000    0.000000  \n",
       "25%      0.000000    7.910400  \n",
       "50%      0.000000   14.454200  \n",
       "75%      0.000000   31.000000  \n",
       "max      6.000000  512.329200  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Taitan_train.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 结果 \n",
    "### 数据规模位891\n",
    "### AGE属性有177个缺失值"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### pclass 与 survived 关系"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "D:\\Anaconda3\\lib\\site-packages\\scipy\\stats\\stats.py:1713: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.\n",
      "  return np.add.reduce(sorted[indexer] * weights, axis=axis) / sumval\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x24089aef048>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.lmplot(x='Pclass', y='Survived', data=Taitan_train)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### age 与 survived 关系"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x240853b4d30>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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ISCElCxERKaRkISIihZQsRESkkJKFiIgUUrIQEZFCShYiIlJIyUJERAopWYiISCElCxERKdTTZGFmF5vZ/Wa22czePc38NWb2TTP7gZndYWav7WU8IiJyfHqWLMysBHwIeA1wFnC5mZ3VVex3gU+7+/nAm4EP9yoeERE5fr28sngesNndH3L3OvAp4NKuMg6MxN/nATt6GI+IiBynXiaLlcDW3PS2+Free4G3mdk24FrgHdNVZGZXmtkmM9u0Z8+eXsQqIiKz6GWysGle867py4G/c/dVwGuBT5jZlJjc/Sp33+juG5csWdKDUEVEZDa9TBbbgNW56VVMvc30C8CnAdz9JqAPWNzDmERE5Dj0MlncAqw3s5PNrEp4gH1NV5lHgVcAmNmZhGSh+0wiIieYniULd28CbweuA+4lvOvpbjN7n5ldEou9C/glM7sduBr4j+7efatKRESeZuVeVu7u1xIeXOdfe0/u93uAF/cyBhEReeL0F9wiIlJIyUJERAopWYiISCElCxERKaRkISIihZQsRESkkJKFiIgUUrIQEZFCShYiIlJIyUJERAopWYiISCElCxERKaRkISIihZQsRESkkJKFiIgUUrIQEZFCShYiIlJIyUJERAopWYiISCElCxERKaRkISIihZQsRESkkJKFiIgUUrIQEZFCShYiIlJIyUJERAopWYiISCElCxERKaRkISIihXqaLMzsYjO738w2m9m7ZyhzmZndY2Z3m9knexmPiIgcn3KvKjazEvAh4FXANuAWM7vG3e/JlVkP/A7wYnc/YGZLexWPiIgcv15eWTwP2OzuD7l7HfgUcGlXmV8CPuTuBwDcfXcP4xERkePUy2SxEtiam94WX8s7DTjNzL5jZt81s4t7GI+IiBynWW9Dmdko4DPNd/eR2RafbpFp1r8euAhYBXzLzM5x94NdcVwJXAmwZs2a2UIWEZEemDVZuPswgJm9D9gFfIKQBN4KDBfUvQ1YnZteBeyYpsx33b0BPGxm9xOSxy1dcVwFXAWwcePGGZOXiIj0xlxvQ73a3T/s7qPuftjd/wp4Q8EytwDrzexkM6sCbwau6SrzeeBlAGa2mHBb6qG5hy8iIk+FuSaLlpm91cxKZpaY2VuB1mwLuHsTeDtwHXAv8Gl3v9vM3mdml8Ri1wH7zOwe4JvAb7v7vuPbFBER6RVzL76rY2brgL8AXkx47vAd4NfdfUsPY5vWxo0bfdOmTU/1akVEntHM7FZ333i8y8/p7yxiUuh+26uIiPyImNNtKDM7zcy+bmZ3xelzzex3exuaiIicKOb6zOKjhL+0bgC4+x2EB9YiIvIjYK7JYsDdb+56rflkByMiIiemuSaLvWZ2CvGP6szsjcDOnkUlIiInlLl+kOCvEf4o7gwz2w48TPjDPBER+REw12TxiLu/0swGgcTdR3sZlIiInFjmehvqYTO7CngBcKSH8YiIyAlorsnidOBrhNtRD5vZB83sJb0LS0RETiRzShbuPu7un3b31wPnAyPADT2NTEREThhz/j4LM3upmX0Y+D7QB1zWs6hEROSEMqcH3Gb2MHAb8GnCh/0d7WlUIiJyQpnru6E2uPvhnkYiIiInrKJvyvsv7v4B4A/MbMrH07r7O3sWmYiInDCKrizujf/qM8FFRH6EFX2t6r/GX+9w9x88BfGIiMgJaK7vhvrfZnafmb3fzM7uaUQiInLCmevfWbwMuAjYA1xlZnfq+yxERH50zPnvLNx9l7v/JfArhLfRvqdnUYmIyAllrt+Ud6aZvTd+U94HgRuBVT2NTEREThhz/TuLvwWuBn7c3Xf0MB4RETkBFSYLMysBD7r7XzwF8YiIyAmo8DaUu7eARWZWfQriERGRE9Ccv/wI+I6ZXQMc+1wod//fPYlKREROKHNNFjviTwIM9y4cERE5Ec0pWbj77/c6EBEROXHN9SPKvwlM90GCL3/SIxIRkRPOXG9D/Vbu9z7gDUDzyQ9HRERORHO9DXVr10vfMTN9raqIyI+Iud6GWpibTICNwLKeRCQiIiecuX421K2E77TYRPioj98EfqFoITO72MzuN7PNZvbuWcq90czczDbOMR4REXkKFX1T3nOBre5+cpy+gvC8YgtwT8GyJeBDwKuAbcAtZnaNu9/TVW4YeCfwvePcBhER6bGiK4uPAHUAM7sQ+CPg74FDwFUFyz4P2OzuD7l7HfgUcOk05d4PfACYeBxxi4jIU6goWZTcfX/8/U3AVe7+OXf/H8CpBcuuBLbmprfF144xs/OB1e7+xdkqMrMrzWyTmW3as2dPwWpFROTJVpgszCy7VfUK4Bu5eUUPx22a1479rYaZJcCfAe8qCtLdr3L3je6+ccmSJUXFRUTkSVY04F8N3GBme4Fx4FsAZnYq4VbUbLYBq3PTqwgfGZIZBs4BrjczCO+uusbMLnH3TXPeAhER6blZk4W7/4GZfR1YDnzV3bMrgwR4R0HdtwDrzexkYDvwZuAtuboPAYuzaTO7HvgtJQoRkRNP4d9ZuPt3p3ntgTks1zSztwPXASXgY+5+t5m9D9jk7tccT8AiIvLUm+vHfRwXd78WuLbrtWm/u9vdL+plLCIicvzm+kd5IiLyI0zJQkRECilZiIhIISULEREppGQhIiKFlCxERKSQkoWIiBRSshARkUJKFiIiUkjJQkRECilZiIhIISULEREppGQhIiKFlCxERKSQkoWIiBRSshARkUJKFiIiUkjJQkRECilZiIhIISULEREppGQhIiKFlCxERKSQkoWIiBRSshARkUJKFiIiUkjJQkRECilZiIhIISULEREppGQhIiKFeposzOxiM7vfzDab2bunmf+bZnaPmd1hZl83s7W9jEdERI5Pz5KFmZWADwGvAc4CLjezs7qK/QDY6O7nAp8FPtCreERE5Pj18sriecBmd3/I3evAp4BL8wXc/ZvuPhYnvwus6mE8IiJynHqZLFYCW3PT2+JrM/kF4Ms9jEdERI5TuYd12zSv+bQFzd4GbAReOsP8K4ErAdasWfNkxSciInPUyyuLbcDq3PQqYEd3ITN7JfDfgUvcfXK6itz9Knff6O4blyxZ0pNgRURkZr1MFrcA683sZDOrAm8GrskXMLPzgY8QEsXuHsYiIiJPQM+Shbs3gbcD1wH3Ap9297vN7H1mdkks9ifAEPAZM7vNzK6ZoToREXka9fKZBe5+LXBt12vvyf3+yl6uX0REnhz6C24RESmkZCEiIoWULEREpJCShYiIFFKyEBGRQkoWIiJSSMlCREQKKVmIiEghJQsRESmkZCEiIoWULEREpJCShYiIFFKyEBGRQkoWIiJSSMlCREQKKVmIiEghJQsRESmkZCEiIoWULEREpJCShYiIFFKyEBGRQkoWIiJSSMlCREQKKVmIiEghJQsRESmkZCEiIoWULEREpJCShYiIFFKyEBGRQkoWIiJSqNzLys3sYuAvgBLw1+7+P7vm14CPAxcA+4A3ufuWXsaUcXeYHIdSaILUgdE9JMOLaLVS7Og+SotX4xNHoDYAzUncEqxVh6QClmDlamedzUnAIangzfFQplTFPYW0hadNkuogjaO78aRCuVzF0xat1jiV2gLcW5QqgzTrh0lKNdwdTxuUKkOY2bTb0WpOAEaa1klKFcAolWqdZVp13FPcU/btv5PFi86l1aqz87HvsXDhWfTV5pOmLR7e8Q3mD61j4bxT2HPgPrbuvZnTV1/KUP8Cduy7jQNHd3D6ytdSKZfYuv8HrF5wHpXKAADb929m19EHOHv5hew5tJ1bd13LOcsvYsXwqew++gibD93L+YsvZKA2yJ7xncyvLGGkbz4AhycP8+/7v8crl/4YjXqTGw7exOuWv+pY/Dfvux+AM0ZWs/nIdu44+AivWnwe8/qHePjoYxyp1zl3/lqSBB7av5NbR3dw2dqNTE5M8tW99/Palc8GnFpS4eGj+2ilKSsH5nOwPs6Nex5l44IVnDQ4wl0HdjFUqrJ+3mJa7lQx7h7dzxkjCwHje/t2cVKtn1WDwzRSZ8fYKGfNX8Roo85QucKDo4cYqdQYqJTZPTHOtqNHec6CRSRJwpYjo6wZGmaoHPrbWL3B7vokS/v6aLlz94EDLKz1sXxggIP1SY40m5w5b96xNnhsfJLhSgkwjjRb7Bmrc+q82PZHx5hoOutGBqinKfceGGPdcD9DlRLN1DlYb7JioEo9dYYrJfaMNxmsGBD61KOjDU4eCX354cOTjFRKLOgrk5izdyKlhDFcTXBSdh1JWVwzquUSE62UZsOZP5CQutFXMcbrTilxwDhabzJ2BJYsKIO32D8Ki0ZKpA5J4jQbUK5A2jJqNWNsLKVcdoyERtNp1lP6Bw2zhMmxlHIVSqUEMydtGZVa+5hoTqTxNwvHIFCqGmkDSrXOY8fdSSfBkvCDgbfCYlYBWlmlYP2GTzqeONYyrM/w8RQvgWFhBJ10KIFb+N0qBu5QSbBS17rrLdwMaznWV8InmnjZsJQwCFVLWBKW8TSFRtyuSoIlSVddTTwxrJlifRV6zdy9NxWblYAHgFcB24BbgMvd/Z5cmV8FznX3XzGzNwM/5e5vmq3ejRs3+qZNm55QbOljW2l+6W/xA4/FQMaARlepFthhnDppzfDmKFknBKBco3LBz1J9/i8AcPjmv+LonZ+i5U1a5Qremgi1lKukFgb9FpAm7c7sQMtiJ4vTaXWAVnOsI5La0EpOedHvM7T4nGOvuafc94P/xfaHPx+SUazTkjKl/kVMTOxlwaJzGZx/Olu2fJ6JdCIbGwCo5+qfbI8bYDAJnWWzGLPQ47wUsPIg+9Kjx16bABq5ZRsGR/N9PM5rAmOlCjsZxKc7Z/GE+eVVHGpUO4NhoF2VJ0CtHZhXgFI4iIFw4VzKrTiX3B2ycyU79v9SXMbBEzrPpeKoQufBDyXMjannXaWpZR0GShXGW56LK193O5oQX9iWxMrhZCb3Oh3bmFve2/NCXPmyRkKVbFglxn2svdJSx3TNw+8G0DIW074VkTgMplDJTc8vQbMZpvtanWsup1CJ22Aefj82P4X+Y9sGSQpVz21hLN/d8iNLjHNfVubBLzcZ29s5jiUe93YKQ6sTVr6ozO4bmkxuS6mmHEsIJSNMN8P6KwmUG2E53ClXU2wyqzuFWgPqsQUthWoDGtn8VqgoC3Qgofq6pZTOHsYbKY0vbCG992DcTodaCvUsM0WDJWwwwfeOQtLi2I7vL1N59RnYihHq/3o7bNsTg4yhrFpI5eVn0bj+Tnz7XmzlYio/8VySBUPtMma3uvtGjlMvk8ULgfe6+6vj9O8AuPsf5cpcF8vcZGZlYBewxGcJ6slIFvWP/yG+Z3ucagFHpvZEDoFNklqdNJmYsa6+n/4ozdY4+699Jw7Uc8dtCjRzY0IDOm78tQzSroHVp8QR1IZXc+7rPn3sCmPno9dx183vmVKumasjjdMN6BjnWvEnm57siqsjeUwzfex1YDSbF+ePdtV1MD8O5uwzOGIwziKY7qrJ52O+kM5BtR/LV+59dA6utVyigDCUZdOlzrq81FnXsUSRzS93BT7N4E8S6vBswJ6tLLFcGMA745wuWZamL+vddefidDByZ5hTkli5M06v5BIF5Nuv5EY1V9f8VkjLmf4U+nJH6UCaW1MLBnNRmofymZKHZJCptjr3cl8rt4UOtWkSRWZBP6QHu16M43DHKUYfpKNQa3bGlZ9O0jCdSTyl5LnAmQwJIluJTXYGSn1qoBWj710n07p1D81v7MjNaObqymvE1xvTnJck2LI+fPs+sNbURQcTGGuPVbZ6CbW3vaw9/QSTRS+fWawEtuamt8XXpi3j7k3gELCouyIzu9LMNpnZpj179jyhoNzTXKKAaXdK9jrgTLNTctI999PY90AsS0ddUwb+qSeas07nTY5uJW2OH5sePXj/tOV8ht/z6067Y5npSCxwrKsfx/INoEVt+kQBdA70c1uRTdmo2TZylunuHTnjum2WeTPrjPOJHoLdCW2medNN5yUdcZW66ppy3dTVWfOlu9Ns0lXWuqaLWmC2qJuj05fvXiY9MrUu86I4C45Q65o3XaANx/c1SHeNdc2YLlFk65ihrlaK7zg0NY7MWOdJrW+9zHLyAAAXkElEQVTfO8M6jk8vk8V0m9u9lXMpg7tf5e4b3X3jkiVLnlhQlmBrTsu9Upmh7cMtC/NZHutYQmnVRmorN3JsCMjVlXjndPdBMmV6lrgHF51NqdK+BbNw6fOmDyn3e8fO9a7XZ8wq00zP4Nj59GzlZ5hXAQaYDPd2p5XdC5hjYAY+ZaPy0y1m3+jcurp35Izr9lnmzawzzvYtxOPTuY1T22Cmst3SjmUbNDumJ7tKN7s6a7Pr946orHM67Vq2aC/PNKwC9C2ZetR073mA0ghgnXWlBXH5lBOZrvupHWeDNn3zDpawZVWSZ43MUleezVxXfwVbOZ8ZR4qh/s6aVi6eYR3Hp5fJYhuwOje9CtgxU5l4G2oesL+HMQFQec0VJKdugFo/VAehtoCpO2AIkiGSgaUk806FwcWhbLkPKgPYwpOpXfx+koXrqCw+g3kXvYfKgpPpG1hOZWQNVhkkqQxQG1pJZWgFVhmgUhkkKbV3aEL7bMasTK0yn/7hteGBdmmApNRPqTLI/BUv5tQXv78jusXLXsDp5/0W/QMrKJUHSZI+SuVBhvpXMDi0FrMSixafz7nn/haLRk6lUmonmmM3MuJRVYOpY5a3fyz3e0c7AifVlna8Npyvy2Ewv2xu+XkO80vDVKx7GMocZlV/P52H9zge/wuVTXRVXM/NgzBshWAqZiQd+7iFdwyQaUcjDJa6D40s2XQO9IazoFqhZFZQNpRfVK1iU4a/6RJGC8MxUmpJOBFJpq272Z6ODwCOtYH5sfIGDCYpQ2WO1VWi0a4nAWgcW9aMGGeYf6TUmQQmLPykhIvDUh8sGDb6KlCpxtuh2aYYTCa5dF2CVrz8SBLwKlRy97gmLdciBo3cslaCUiWUX7G+xLMvqbHotFJ4UJ1JoFGGZAAqQ8bi80qsfn2V/lUJjQrQD1YBq0FrISQLDKtC2gfNpWDzgBqkfYYvSWDIwkHSX8EWV6DfoGYwWMUWVcLvVYNyNTRGAlQNW1Oj9pYVWDmhdP4iShcug+EK1BLoq2KLBqC/FB6UVBKolbBV87FlwyHAahkqJaiWYOUI1cs2ULlkA6xeHBqxlIT5fRVK562l+qYLsdVLIDFs9RIqP/Fcnky9fGZRJjzgfgWwnfCA+y3ufneuzK8Bz8494H69u182W71PxjMLEZEfNU/0mUXP3jrr7k0zeztwHeFk9mPufreZvQ/Y5O7XAH8DfMLMNhOuKN7cq3hEROT49fTvLNz9WuDartfek/t9AvjpXsYgIiJPnP6CW0RECilZiIhIISULEREppGQhIiKFlCxERKSQkoWIiBRSshARkUI9+wvuXjGzPcAjwGIg/0lZs00/nrKq68mt65kSp+pSXc/UOOdadq27H/+H67n7M/KH8Ffgc5p+PGVV15Nb1zMlTtWlup6pcT7eZY/3R7ehRESkkJKFiIgUeiYni6sex/TjKau6nty6elm36lJdvayrl3U/nXUdl2fcA24REXnqPZOvLERE5KnyZDwlf7J/gIuB+4HNwMdyv7+7a94/EL5Aaw9QBw7Ef7OvPWsSvmRrlPbXi9Xj9NE4f5LwlWv7aX+XZyOuqwTsjmWz5SaBI8AFhO8Pr8flH45xTMY69gL74jJjcV3NWGZ/Ls4JYFdu2oHr4zon4zrycR3Obce7Y1tk01+Kv2f1PBJjbdH+orPs31aurhR4FNiSa7tGXPdYrHuS9lfPZW2db+c0tkEr/n4wt740Lt+KP43c9taBrwKP5bbjjq5lJ+JPoyv+NP5bz23HQWA8F9uhOJ214ZHc/kxz65nIxZe111jXug7TGdd4fC2bPxZ/nyR8C2TW58YJXwSW9cOUdh+ox/qyefUYaxZvmiuT38as3mxffTu2f9Zed+T2Z9Z3GzE2j9PZNjQJfTUrewvh+JqI25dteyO+lu3LCcK3X2Z9YzxOZ22btd+R3L7K4q3nyk127aNsftYezdy/aW6Z/E++v3X383zb1eO25r5isKP/ZPt/c659W3Fbsn7TzNWbj9njvw/kti2bPhJfG8+ts5Vbvp7bBs+tI/vJ94VsGQfuzbVBtux9hONze9xv2dh5BfDD+HMF8Dtx3v3AqwvH5ac7MUyTKErAg8CzgL7YCD9O+FLs2wmD2rOAhbkd8CCwNG70zjj/vNjIDwHvio2W7fwrYplfAT4BnBrLbiJ8W+j9cYf8PaHzf5Ew6OyOMb45drjr4/Rbge8AXyZ8TWwrxvRl4Ctxx20hHKBfA/41xrIr1rUj/v4A8P0Y86/GjvAQ8Bng03FbdwAfIQw298T22R13+mjsZFcTBt8tsT1+ndDRU+C1hG8vvCt2pn+JdTxEGOC2A7cBd8bt+BLwvwhJrgF8KMbosV3/PLbFBCFBvgFYS7tT/xnh63LrwD8Bfxu3K6vrb2kno63Aq2gfGB8A/jthENwFXAJ8K677irjPT4t1fTZuQz3Gelf8mYzxHSH0o7G4L+8Drox1XQvcCrwtbsdX4ronYnu+DVgf6xoFPkjoJ5tiff8tzk8JfeX3Y1tmA2aFcIAeirG+Pda1Gfilrn3wzthOE3F718f9OBm3/bH4+1j82Ur4grEDcZ3fJfSt/XH6BzGOm2O7T8Q2+kfgC7GOg8DngU/Gug7Gf2+I7XM07vMsefw24TicJByTn6Z9YvEQ8EeEPpudkB2O9R2NcR2NsW2JbXJDXOddcTv+Odd+Pwm8PpZtEvrLn8f1tAj7/Vm0E/nfA++Nse0E/iKus0k4zv9DjLNBOOFbGbchJZxcvYYwBo3F7X1VrOtewjG9K8Z/bVzX1lj3F4B+4O7YvtcDC2Kck3G/nEo7QV8X49sKrItxjcdtOhf4a9oncd+LbdSI7fWpWCZLZCuAc+L274v78vIY7z8S+ttdcV0LY1xb42s14ORYtvRMe+vs84DN7v4QcD5hB17g7nXgRmAiznsP8O+ErxT+pLvvBr4BjMb5t8f66sCLCAN05uuxzEeAS2l/xe+/EQ7s/MD6sbhMFZg0s+WEHb2QkJkhHNzPAT4OvITQeRYTBo4lhI6ykDDQ3EAY4MqEAeyzhJ1nMdbDhNuDtwBDMaZPxvVPEAbC7AykRuhwdcLA+e24LYdi/JsJnfeVhITSIgzcDxI69l3A82O8mwkHyAJCEvp2XN85hI787RjvvwPPjvMWAX9M+4uy73X3z7n7I7S/b30pcFaM+Uhc7nrCAdRHe0DeEeN7R9ym7Euts8F+E2HQ/v247afHfb6IMMBcSEh0B2mf+R7MxVHLbdMuwoF7dZy3NW5T1pafIfS97Iz5K7Hu7GzwEKGfLIrtNkjoY5OE/T1O5y3eGrCGkBQgDF5O6KO/BPyPWHc1buMmQl95zN1/SDsJboivjxMGtErcH0sIyWAF8LtxG++M09fGuIZj+2dn8KsJA2l2ArWBMEAtISSkUwhJ/2hc1zLCycBRwtX9PblteDXhWGgSTrSeB/xV3G8lQl/fHpdP4rbcR7vPXRC38c4Y47lxWSccz/8cyzaAb8YYb6d9hfSBuI8gHD+nEk54spPNvXHZg8DP0D7ZecTdtxMGXyMcIyPARTHuUoxnK7AcWEU4LkvALwAviOtJgPe7+3hsFwO2u/sBwvFXIiTtq2Jd2YnvLmCHu2+JcW2L23tHbNODhL69KG7T3vhzftwf+Svv7LgoAT8W17OZcGLzH2Lb7nD3/TGuHcCd7j7p7g/Hss9jFj39przjtJKwodnvO+K/EC/Pzex8QmffTDhbXGNm3yGcYdRj2V8mNORNhG/jmyB0nhT4tpn9OnA64SC6izAIXEYYrP6Z0GG3EQ4cCDthASEhfYawY/6rma0lnJVml+pvICSmNwD/kzAwnh7rh5CAFhMHQw9fP5sSBpw9scxuQmcox7b4eeDrhIP0jLgdY4QDpUIYkJuEjpVZREgEhwgdfjDW97eEs7SR2J7ZAPDCXPt8A3hxnF4YY78PGCBcLZVjuaPuvtPMBgkHwH0AZrYOmB/LvTBu8/z4+0sJV1eDcfqquA17CQPqaJwH8LOxzcuE2ypl4HWx7X7TzLIkNkw483svIbm2Yp0nxbbJLvf3Ea5Shgj7cydhP14ay3851vObsZ0fjfvhm4Szr22ERP8uwmX9HXEdlxH6nsd2f0dcL4SkfJiQIL5OuCL6h9h+zyIkqaz/LCf09ecSBvH3xv51Wly+SkgAldgWTkhSZcLZaXark7hMM+6/EqFPvyXOqxEGl+x2zvLY7p8lnEyMAx+NcQzGOm4lHGsVQv9YHH9/U4zj5YT+cRHhrDaN8yEcQ1fE37Pj4AWEfjgQ15FdITbjtkwS9vOHzOxojNmBv8y1axLXN0A4hiEc64sJ40CZ0IeyfXFfXNe+OO9hM9tGSFQQToyujnGUCcfT5+N6SrH9L4y//wkhoQ7EuH7PzFYR9r8Bq81sV276bEJCzsan1xBOolIz+zhwJqEvlc3sBkK/uz2219q4vTcREuUKwh2JCcKxvT3GAKFvNwkJYiuhz66knXwz3jWdlZvRiXhlYdP87l3Tf0Y4YLPpNYRO81VghZm9APgDwhn9WbHMcuAXaZ/9/BNhB+0gDApNwlneBYSDPxtkMw8TziLeQdhRBvyTu59PGGwrhE50KWGn748xtghXE8OEjnM7c+NxHS+NsX2e0Dl+QLg1tIxweWqEgX9P/N0JyewBwq2xibjtWQf/v7H8AsKAeA1hMPhWXOa/Eq4W3kb7Nh+Es5UttK8itgITZjZEOJDHCYl8CPgc4YrwPkLSHY1xfAn4jRjPVsIA9gHC2VpKSCjnEs6GDwE/Qbh9kz03WUUY8D4ft2MBYZ8ejNt8dWyfBwj7aoSQAHbF6ZsIt3VqcX2rCAfJV2hf4i8D/nOMfV5s05fFsmuAm9y9jzA4bgD2uvt6QqLKbnUejW39SJy+LW7bs+O2LCQMhiOE/vG+uA1Xx7huJAxM1xNvd8bl30tIOIcJZ6wfim2wkvY9eAh9MbuHvZb28yuP87IrAuLyW919LSEBetxXPxHXUY3lriQM+tnzt/1xHQ8Q+tY5cbkDhH5PjPnBuE+yJH5Vrr3PJByzLcIxeRohUY/G6Rbwp4SBdU2s+5ux3FhsmwohYZ4b43oZ4divx23+Bu1ngNlV1hJCv3oFYbC/kHDi+VHCLdsk/mS3h+cTBmEnjCll2rckW7HsZ+NYMBzb47fdfRlhIE8Ix9o7Cfs3Af4/Qp/dSzgRWUVIZDcRrtKyE8X8Pt1M2yVxG0cIVzOrY1tndx9+LsYC7bEknxy6p5lmusOJmCy2ETY8+30F7VsJZcKBfg6hA1xB2DHnEQ7crCP/E6Ej3UXokF9w9wbhQDPCJd/VhI63iNBJDhISztWEM435hMu99xMGhuEY1920b2ltif/+S4zjwhhzdgBlZ3QN2p17P+2HuZhZmbAfjubaYGksUyEcBG+NryeEM4wfxLa4nDD4VQkH0CWxfT4e55cJnb1EGGDmERJM9qByLeFW2XzCgVUhDEDzCLc19se2qBA6/aG47WmM4zHaz1+OEAbazxEO9GWEAfNzsX32ExLuOwgH6gThSqkUt/H8uB1nxe0YJlw1fIZw26AeX/sM4cprE2HQfZhwJvnqOP/mGO/LY3s9GuM7x91fTkgC2QPDI7Gu5bF9s6R1adyP2W0UCAkkjbFA6CtZIoVwIGcPitcQ7hMvJVydnZuroz/GPk77ltA/EvZ/dmX4KUJ/WR6XrdDe92fF9Z5MuJ8/FJdZFNvvU4QBcHWcfnn89/8QksoAoV98n7Dv+oClZraFkLRKsa71hJOnkVw7riQMaJcBPxXjOYNwTG2I85YSrkr/Kda9hnCW+4K43ucSbqncSuhzB+K2Wmzz8+I+KcXtPDvebpwg7O+3xuldhGNoGeG4Hon1Z88CsttH2b39PXG6FJcddveb4z6rxe27IrbTvXGZdYTnmrtpvxkmu0pdG1/fGdv/bjO7IraVu/v34uvZ1etCwp2GRfH1P4nrPRDr6yP0ASckMyf0535CP5nIlRuL+68c41kd23NV3L8rCLedTo+vZeNn93ifn86Xm9aJmCxuAdab2cmEM7K1wK1mViWcQdQIHe40wkDRIDTcHYQDuI8w4GflAbaaWXYmnWXUlxIent5GSBr9hAP8atoPzd9EGPhuIDzEy24pvI6w894Z6387oVO8hXCm/jJCR7qEcPYCobOOEB7WfS3GPQS8kdB5J2O5EUJHPyvOn6CdIPsIA/lzYhzZg99dMc7s3UhvJ3T29bGeLYSO9+OEQa0Wf1qEDtcgPMjrJ1xh7I/rXkroI/cROvDZsczthIP0TbGdxwjJ5OJY13NiG14c2+UPY13vJAymQ4SBp0G4StgSfx8l7NfsgflnCMlrFeGWWvag8sdp3+oYjDE+FOt5Vax7kjAA/Bjh7HmbmY3QfnPEnTGec+I23Eu4qlxIuAK4LtZjhEHk0thWN5nZL8ZpA5ab2XMICXxxjO+jhMSavQFhHe13wo0T+k/+5OMtcRsPEvrNSbTPCh+M8Rjtk5iFhNusf0pIjlnS+Q7hRGEyrv82wkNYJzz3+ps4r0F4XrEjLjtMeK71G3H+YcK97rfEZcdiDPvjPvprwsnaRNzG2+K/43EbbyPc0moRktohwkkXhGcsj8b9vIJwjH6NcEsn+7k+7rM+YIeZvTW27VHgTDNbGevtI1yZnEf7/v0vxn23IpZ/hDBorog/D8b9WjazlxOOtxLhamcH4ZhdF7d7d9yWk2i/AeY5hP62IC5zRtyuKwhX5XXCraXX58Ycj/vmWbFsSjhG1xP2ezm2XTm+9qtxPzyHcLxXCYnuRYRkM04Yj2qE/n8eYexrEvrQVwnH/aK4ni/G/bfSzBbEuFYCzzazWhxr1xP60oxOyD/KM7PXEt7xUCKcXb6Q0Fm+RBjMP0HYKR8kDFinE3ZgNrBm93P3EQ6y8bh8f241k7Fsg/agmT3Dyd7NdD3hzGRDrCe7PN1FOEP+x1jHKOFS+VuEA6MV17mE9gO+JNaR3Seu0j5rPRKns0v+7LIR2petTDPvMOHMZG1uejBXb/auIsu9lm1fEufly44SOmdWph7brBHryNq1mZvOljU6byG2Yt2eK5NN59ebvR04O+Oqx/ZYOM2yjfhvkivbijFOF1f21kly66vnls+2JyHskxKd7dGivU8gDJr9tE84sumE9tsmK/HfI4S2LMW6byQc1Atov520Fudnb27oo32vvUG7f2btWaXdf7LnFtlV0s2EvjoQyx8h7M9lcR3ZO7OyK4usL+b3bXYrK7sF2xfXuZj27bX5tN+2mb2zZ5j2m0T2xTLVWE85/rsyt56sX2bPlvK30Gq092O+z07QeYyOxt/7Yvm7Ccdpdnw0cu2VHUNJfH0P4djMbsllz6YqcdmxWLZK+zjJ+hGxTD7u7JkGtJNtdnWQvUki60cHCCdO+bfqZn16E+FKbBnhqn0/4Tg4KW5/9m6y9XG57Hgz2lc8fcR3NhH2y/y4fR+L9bwt1vEHhOT58zG+X3f3LzOLEzJZiIjIieVEvA0lIiInGCULEREppGQhIiKFlCxERKSQkoWIiBRSshB5HMzsp8zMzeyM4tIi/+9QshB5fC4n/O3Pm5/uQESeSkoWInMUP/fqxYRPHH1zfC0xsw+b2d1m9kUzu9bM3hjnXWBmN5jZrWZ2XfzEYpFnJCULkbn7SeAr7v4AsD9+zMfrCR8P8WzCR028EMDMKoTPGXqju19A+AvaP3g6ghZ5MpyIH1EucqK6nPAxNBA+sO9ywsc+fMbdU2CXmX0zzj+d8LlT/2Zm0P5IdJFnJCULkTkws0WET3A9x8yyL5lx2l9oNGUR4G53f+FTFKJIT+k2lMjcvBH4uLuvdfd17r6a8Cm/e4E3xGcXJxE+/RPCpwAvMbNjt6XM7OynI3CRJ4OShcjcXM7Uq4jPET65cxvhu1M+Qvi+kEPxa4DfCPyxmd1O+KjrFyHyDKVPnRV5gsxsyN2PxFtVNwMvdvddT3dcIk8mPbMQeeK+aGbZdzi8X4lC/l+kKwsRESmkZxYiIlJIyUJERAopWYiISCElCxERKaRkISIihZQsRESk0P8PyfxAPAL+bwoAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.swarmplot(x='Age', y='Survived', data=Taitan_train,)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Parch，SibSp，拥有父母孩子 与 survived 关系"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x2408a067550>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.swarmplot(x='SibSp', y='Survived', data=Taitan_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x2408a1520b8>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.swarmplot(x='Parch', y='Survived', data=Taitan_train)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 这里可以看出，如果乘客拥有的父母和孩子过多他的生存率就会下降。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Taitan_train.hist(bins=50, figsize=(20,15))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 未发现明显关系\n",
    "### 使用correct（）观察"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>PassengerId</th>\n",
       "      <th>Survived</th>\n",
       "      <th>Pclass</th>\n",
       "      <th>Age</th>\n",
       "      <th>SibSp</th>\n",
       "      <th>Parch</th>\n",
       "      <th>Fare</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>PassengerId</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.005007</td>\n",
       "      <td>-0.035144</td>\n",
       "      <td>0.036847</td>\n",
       "      <td>-0.057527</td>\n",
       "      <td>-0.001652</td>\n",
       "      <td>0.012658</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Survived</th>\n",
       "      <td>-0.005007</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.338481</td>\n",
       "      <td>-0.077221</td>\n",
       "      <td>-0.035322</td>\n",
       "      <td>0.081629</td>\n",
       "      <td>0.257307</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Pclass</th>\n",
       "      <td>-0.035144</td>\n",
       "      <td>-0.338481</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.369226</td>\n",
       "      <td>0.083081</td>\n",
       "      <td>0.018443</td>\n",
       "      <td>-0.549500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Age</th>\n",
       "      <td>0.036847</td>\n",
       "      <td>-0.077221</td>\n",
       "      <td>-0.369226</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.308247</td>\n",
       "      <td>-0.189119</td>\n",
       "      <td>0.096067</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SibSp</th>\n",
       "      <td>-0.057527</td>\n",
       "      <td>-0.035322</td>\n",
       "      <td>0.083081</td>\n",
       "      <td>-0.308247</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.414838</td>\n",
       "      <td>0.159651</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Parch</th>\n",
       "      <td>-0.001652</td>\n",
       "      <td>0.081629</td>\n",
       "      <td>0.018443</td>\n",
       "      <td>-0.189119</td>\n",
       "      <td>0.414838</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.216225</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Fare</th>\n",
       "      <td>0.012658</td>\n",
       "      <td>0.257307</td>\n",
       "      <td>-0.549500</td>\n",
       "      <td>0.096067</td>\n",
       "      <td>0.159651</td>\n",
       "      <td>0.216225</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             PassengerId  Survived    Pclass       Age     SibSp     Parch  \\\n",
       "PassengerId     1.000000 -0.005007 -0.035144  0.036847 -0.057527 -0.001652   \n",
       "Survived       -0.005007  1.000000 -0.338481 -0.077221 -0.035322  0.081629   \n",
       "Pclass         -0.035144 -0.338481  1.000000 -0.369226  0.083081  0.018443   \n",
       "Age             0.036847 -0.077221 -0.369226  1.000000 -0.308247 -0.189119   \n",
       "SibSp          -0.057527 -0.035322  0.083081 -0.308247  1.000000  0.414838   \n",
       "Parch          -0.001652  0.081629  0.018443 -0.189119  0.414838  1.000000   \n",
       "Fare            0.012658  0.257307 -0.549500  0.096067  0.159651  0.216225   \n",
       "\n",
       "                 Fare  \n",
       "PassengerId  0.012658  \n",
       "Survived     0.257307  \n",
       "Pclass      -0.549500  \n",
       "Age          0.096067  \n",
       "SibSp        0.159651  \n",
       "Parch        0.216225  \n",
       "Fare         1.000000  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Taitan_train.corr()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Survived       1.000000\n",
       "Fare           0.257307\n",
       "Parch          0.081629\n",
       "PassengerId   -0.005007\n",
       "SibSp         -0.035322\n",
       "Age           -0.077221\n",
       "Pclass        -0.338481\n",
       "Name: Survived, dtype: float64"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Taitan_train.corr()['Survived'].sort_values(ascending=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# PART1 继续数据探索（2\n",
    "### 使用pandas的可视化查看各属性之间的关系"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "D:\\Anaconda3\\lib\\site-packages\\ipykernel_launcher.py:2: FutureWarning: 'pandas.tools.plotting.scatter_matrix' is deprecated, import 'pandas.plotting.scatter_matrix' instead.\n",
      "  \n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "array([[<matplotlib.axes._subplots.AxesSubplot object at 0x000002408ACC4B70>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000002408ACEFD68>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000002408B228FD0>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000002408B2592E8>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000002408B280860>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000002408B2A9DD8>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000002408B2D6390>],\n",
       "       [<matplotlib.axes._subplots.AxesSubplot object at 0x000002408B2FE940>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000002408B2FE978>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000002408B355438>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000002408B37D978>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000002408B3A4EF0>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000002408B3D54A8>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000002408B3FBA20>],\n",
       "       [<matplotlib.axes._subplots.AxesSubplot object at 0x000002408B42B080>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000002408B456518>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000002408B47DA90>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000002408B4AC048>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000002408B4D35C0>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000002408B4F9B38>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000002408B52A0F0>],\n",
       "       [<matplotlib.axes._subplots.AxesSubplot object at 0x000002408B551668>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000002408B579BE0>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000002408B5AB198>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000002408B5D2710>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000002408B5F8C88>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000002408B629240>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000002408B6507B8>],\n",
       "       [<matplotlib.axes._subplots.AxesSubplot object at 0x000002408B676D30>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000002408B6A92E8>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000002408B6CE860>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000002408B6F7DD8>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000002408B728390>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000002408B74D908>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000002408B776E80>],\n",
       "       [<matplotlib.axes._subplots.AxesSubplot object at 0x000002408B7A7438>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000002408B7CE9B0>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000002408B7F7F28>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000002408B8274E0>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000002408B84CA58>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000002408B875FD0>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000002408B8A4588>],\n",
       "       [<matplotlib.axes._subplots.AxesSubplot object at 0x000002408B8CCB00>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000002408B8FD0B8>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000002408B924630>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000002408B94DBA8>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000002408B97D160>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000002408B9A26D8>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000002408B9CCC50>]],\n",
       "      dtype=object)"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 864x576 with 49 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from pandas.tools.plotting import scatter_matrix\n",
    "scatter_matrix(Taitan_train, figsize=(12, 8))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 未发现过于明显的相关性关系，下一步将文本数据转化位数字处理做进一步观察"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 登船港口与存活度琴状图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "D:\\Anaconda3\\lib\\site-packages\\scipy\\stats\\stats.py:1713: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.\n",
      "  return np.add.reduce(sorted[indexer] * weights, axis=axis) / sumval\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x2408a1eeb70>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.violinplot(x='Embarked', y='Survived', data=Taitan_train)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 经过上面的可视化探索，仅发现拥有亲友的数目会影响乘客的存活率，在对其他属性的探索中没有发现其与存活率的明显关系。下一节将从数学的角度继续探索，并处理数据以符合模型需求。"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
